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xLiD-Lexica: Cross-lingual Linked Data Lexica

Various associations between linguistic elements and linked data resources across languages

Contact persons: Lei Zhang, Michael Färber

https://km.aifb.kit.edu/sites/xlid-lexica

Research group: Web Science




Description

In this work, we constructed cross-lingual linked data lexica, called xLiD-Lexica, by exploiting the multilingual Wikipedia and linked data sources, especially DBPedia. First, we provide the reference association between entities and labels, where labels are phrases can be used to refer to entities. The reference association of each pair of label and entity captures the relationship in the sense that to which extent the label refers to the corresponding entity and thus it is an intended sense of the label. Besides that, we also provide the co-occurrence association between entities and labels, where we utilize labels that co-occur with an entity in its immediate context to derive their co-occurrence frequency. Apart from labels, there are many more words contained in Wikipedia for different languages, which could be important resources for many tasks. Therefore, we also derive the co-occurrence association between entities and words. In order to derive such associations between entities and words / labels across languages, cross-language links that connect Wikipedia articles describing equivalent entities have been employed.


Contributors
Achim Rettinger, Steffen Thoma, Lei Zhang, Michael Färber


Publications

inproceedings
Lei Zhang, Michael Färber, Achim Rettinger
xLiD-Lexica: Cross-lingual Linked Data Lexica
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), Seiten: 2101-2105, European Language Resources Association (ELRA), Mai, 2014
(Details)


Lei Zhang, Achim Rettinger, Steffen Thoma
Bridging the Gap between Cross-lingual NLP and DBpedia by Exploiting Wikipedia
Proceedings of the NLP&DBpedia workshop co-located with the 13th International Semantic Web Conference (ISWC 2014), CEUR-WS, Oktober, 2014
(Details)


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Projects
XLike; XLiMe;